Evidence map›Paper›PMID 42011032›Full record

ArticleImmunity, inflammation and disease2026

Antimicrobial Peptides and Systemic Inflammation: A Network Analysis.

Fabiano Pinheiro da Silva, Francisco Garcia Soriano, Ludhmila Abrahão Hajjar

Abstract read
In one paragraph

Article in Immunity, inflammation and disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Fabiano Pinheiro da SilvaLaboratório de Emergências Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-2673-2202
Francisco Garcia SorianoLaboratório de Emergências Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.
Ludhmila Abrahão HajjarLaboratório de Emergências Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAntimicrobial peptides (AMPs) are essential components of the innate immune system, exhibiting diverse mechanisms of action.

objectiveThis study investigates the roles of cathelicidin (LL-37), alpha-defensins, and the S100 proteins S100A8 and S100A9 in systemic inflammation associated with sepsis, severe COVID-19, and acute pancreatitis using whole-blood bulk RNA-sequencing data.

resultsGene co-expression network analysis revealed that during septic shock and severe COVID-19, cathelicidin and alpha-defensins act synergistically in innate immune responses, while S100A8 and S100A9 function through distinct pathways related to mitochondrial metabolism and ubiquitin ligase binding. In contrast, the acute pancreatitis network displayed a different pattern, with CAMP co-expressed alongside S100A8 and S100A9, whereas alpha-defensins were downregulated and associated with inhibited mucosal immune responses.

conclusionThese findings suggest that antimicrobial peptides contribute variably to systemic inflammation depending on the underlying insult, underscoring their complex, context-dependent roles in critical illness.

Indexed as

alpha-DefensinsAntimicrobial Cationic PeptidesAntimicrobial PeptidesCOVID-19InflammationPancreatitisSepsisCalgranulin ACalgranulin BCathelicidinsGene Regulatory NetworksHumansImmunity, InnateSARS-CoV-2Shock, Septicalpha-DefensinsAntimicrobial Cationic PeptidesAntimicrobial PeptidesCalgranulin ACalgranulin BCAMP protein, humanCathelicidinsS100A8 protein, humanS100A9 protein, humanantimicrobial peptidesgene expressiongene networksinflammation

Identifiers

PMID42011032
PMCPMC13096716

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.